Abstract
The frequent pattern tree (FP-tree) is an efficient data structure for association-rule mining without generation of candidate itemsets. It was used to compress a database into a tree structure which stored only large items. It, however, needed to process all transactions in a batch way. In real-world applications, new transactions are usually incrementally inserted into databases. In the past, we proposed a Fast Updated FP-tree (FUFP-tree) structure to efficiently handle new transactions and to make the tree update process become easier. In this paper, we attempt to modify the FUFP-tree construction based on the concept of pre-large itemsets. Pre-large itemsets are defined by a lower support threshold and an upper support threshold. It does not need to rescan the original database until a number of new transactions have been inserted. The proposed approach can thus achieve a good execution time for tree construction especially when each time a small number of transactions are inserted. Experimental results also show that the proposed Pre-FUFP maintenance algorithm has a good performance for incrementally handling new transactions.
Original language | English |
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Pages (from-to) | 9498-9505 |
Number of pages | 8 |
Journal | Expert Systems With Applications |
Volume | 36 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2009 Jul |
All Science Journal Classification (ASJC) codes
- Engineering(all)
- Computer Science Applications
- Artificial Intelligence